by teknovizier
Facilitates AI‑enhanced interaction with Tekla Structures, enabling automated selection, component insertion, property management, and view operations via natural‑language commands.
Tekla MCP Server acts as a bridge between AI agents or MCP‑compatible clients and Tekla Structures. It exposes a set of tools and resources that allow users to control modeling tasks—such as selecting objects, inserting components, adjusting properties, and manipulating views—through plain‑text instructions.
Q: Which Tekla versions are supported?
A: Tested with Tekla 2022 and Tekla 2026; other versions may work but are not officially verified.
Q: Do I need a specific AI model?
A: Any MCP‑compatible client can be used; the server has been validated with Claude Sonnet 4.6, Gemini Flash, GPT‑4o, and several open‑source models.
Q: How are plugins added?
A: Develop a Python module that follows the component handler interface and register it in the server’s configuration file.
Q: Is the project open‑source?
A: Yes, it is released under GPL‑v3.
Q: Where can I find full documentation?
A: See the docs folder in the repository for Reference, Quickstart, Configuration, Testing, and Distribution guides.
This server facilitates interaction with Tekla Structures, helping users automate and accelerate modeling workflows. It acts as a bridge between AI agents or MCP-compatible clients and Tekla, exposing resources and tools for selection, component insertion, property management and view operations.
📌 What is MCP?
MCP stands for Model Context Protocol, and it is a communication protocol introduced by Anthropic to enable more efficient and secure interactions between large language models and other systems, such as human users or other AI agents.
Tekla MCP Server uses AI-powered natural language processing to make interactions more intuitive, allowing user to work with tools using plain text.
To use this server, one must first install and configure an MCP client.
Modular Architecture: Powered by FastMCP 3.0, with toolset organization through modular providers (Selection, View, Properties, Components, Operations, Drawing).
Resource Discovery: Auto‑detection of available filters, macros, components, and custom requirements and instructions.
Component Handler Plugin System: Flexible plugin model for Tekla components with lifecycle hooks, e.g., Lifting Anchors component select anchors based on element weight and auto‑calculates anchor placement according to center of gravity.
LLM‑Powered Component Property Understanding: Natural language mapping like "concrete cover thickness" → actual Tekla component property.
Semantic Attribute Mapping: Hybrid semantic system (MiniLM + LLM fallback) for mapping user‑friendly names to Tekla attributes.
See Reference for complete list of tools and resources.
The server was tested to work with Tekla 2022 and Tekla 2026 and may not be compatible with other versions of Tekla Structures.
Verified to work correctly with Claude Desktop, DeepChat and Goose clients, along with the following language models:
For complete setup instructions, see Quickstart Guide.
| Guide | Description |
|---|---|
| Reference | Tools and resources reference |
| Quickstart | Setup and first steps |
| Configuration | Config files and environment variables |
| Testing | Running tests |
| Distribution | Building portable binary |
This software is open-source and released under the GPLv3 license. You are free to use, modify, and distribute it, as long as all modifications remain open-source under the same license.
For full details, please refer to the LICENSE file included in this repository.
This software is provided as is, without any warranties or guarantees of functionality, reliability, or security. The developer assumes no responsibility for any damages, data loss, or other issues arising from its use.
Use at your own risk.
Please log in to share your review and rating for this MCP.
Explore related MCPs that share similar capabilities and solve comparable challenges
by activepieces
A self‑hosted, open‑source platform that provides a no‑code builder for creating, versioning, and running AI‑driven automation workflows. Pieces are TypeScript‑based plugins that become MCP servers, allowing direct consumption by large language models.
by Skyvern-AI
Automates browser‑based workflows by leveraging large language models and computer‑vision techniques, turning natural‑language prompts into fully functional web interactions without writing custom scripts.
by ahujasid
Enables Claude AI to control Blender for prompt‑assisted 3D modeling, scene creation, and manipulation via a socket‑based Model Context Protocol server.
by PipedreamHQ
Connect APIs quickly with a free, hosted integration platform that enables event‑driven automations across 1,000+ services and supports custom code in Node.js, Python, Go, or Bash.
by elie222
Organizes email inbox, drafts replies in the user's tone, tracks follow‑ups, and provides analytics to achieve inbox zero quickly.
by grab
Enables Cursor AI to read and programmatically modify Figma designs through a Model Context Protocol integration.
by CursorTouch
Enables AI agents to control the Windows operating system, performing file navigation, application launching, UI interaction, QA testing, and other automation tasks through a lightweight server.
by ahujasid
Enables Claude AI to control Ableton Live in real time, allowing AI‑driven creation, editing, and playback of tracks, clips, instruments, and effects through a socket‑based server.
by leonardsellem
Provides tools and resources to enable AI assistants to manage and execute n8n workflows via natural language commands.